Fast mining of non-derivable episode rules in complex sequences

Researchers have been endeavoring to discover concise sets of episode rules instead of complete sets in sequences. Existing approaches, however, are not able to process complex sequences and can not guarantee the accuracy of resulting sets due to the violation of anti-monotonicity of the frequency metric. In some real applications, episode rules need to be extracted from complex sequences in which multiple items may appear in a time slot. This paper investigates the discovery of concise episode rules in complex sequences. We define a concise representation called non-derivable episode rules and formularize the mining problem. Adopting a novel anti-monotonic frequency metric, we then develop a fast approach to discover non-derivable episode rules in complex sequences. Experimental results demonstrate that the utility of the proposed approach substantially reduces the number of rules and achieves fast processing.

Highly efficient serial episode discovery in streams and complex sequences

This research proposed a series of methodologies and algorithms for highly efficient serial episode discovery in streams and complex sequences, and applied the developed techniques to quantitative analysis of the effects of price promotions. This research has outputted nine ERA ranking AlB papers published in international journals and conferences.

Mining condensed sets of frequent episodes with more accurate frequencies from complex sequences

Many previous approaches to frequent episode discovery only accept simple sequences. Although a recent approach has been able to nd frequent episodes from complex sequences, the discovered sets are neither condensed nor accurate. This paper investigates the discovery of condensed sets of frequent episodes from complex sequences. We adopt a novel anti-monotonic frequency measure based on non-redundant occurrences, and dene a condensed set, nDaCF (the set of non-derivable approximately closed frequent episodes) within a given maximal error bound of support. We then introduce a series of effective pruning strategies, and develop a method, nDaCF-Miner, for discovering nDaCF sets. Experimental results show that, when the error bound is somewhat high, the discovered nDaCF sets are two orders of magnitude smaller than complete sets, and nDaCF-miner is more efficient than previous mining approaches. In addition, the nDaCF sets are more accurate than the sets found by previous approaches.

Quality of pre-school children's pretend play and subsequent development of semantic organization and narrative re-telling skills

Purpose: This study investigated if the quality of pre-school children's pretend play predicted their semantic organization and narrative re-telling ability when they were in early primary school. It was hypothesized that the elaborateness of a child's play and the child's use of symbols in play were predictors of their semantic organization and narrative re-tell scores of the School Age Oral Language Assessment. Method: Forty-eight children were assessed using the Child-Initiated Pretend Play Assessment when they were aged 4-5 years. Three-to-five years after this assessment their semantic organization and narrative re-telling skills were assessed. Results: Results indicate that the elaborateness of a child's play and their ability to use symbols was predictive of semantic organization skills. Use of symbols in play was the strongest play predictor of narrative re-telling skills. The quality of a pre-school child's ability to elaborate complex sequences in pretend play and use symbols predicted up to 20% of a child's semantic organization and narrative re-telling skills up to 5 years later. Conclusions: The study provides evidence that the quality of pretend play in 4-5 year olds is important for semantic organization and narrative re-telling abilities in the school-aged child.

The taxonomy and phylogeny of the Cherax destructor complex (Decapoda : Parastacidae) examined using mitochondrial 16S sequences

This study uses nucleotide sequences from the 16S rRNA mitochondrial gene to investigate the taxonomy and phylogeny of freshwater crayfish belonging to the 'Cherax destructor' complex. The sequencing of an approximately 440-bp fragment of this gene region from freshwater crayfish sampled from 14 locations identified significant haplotype diversity. Phylogenetic analysis found three distinct clades that correspond to the species C. rotundus, C. setosus and C. destructor. C. rotundus is largely confined to Victoria, and C. setosus is restricted to coastal areas north of Newcastle in New South Wales. C. destructor is widely distributed in eastern Australia and shows significant phylogeographic structure, with three well supported clades. None of these clades, however, correspond to species previously recognised as C. esculus, C. davisi or C. albidus. The failure to genetically distinguish these morphologically defined species is consistent with reproductive information and morphological plasticity relating to habitat similar to that documented for other Cherax species.

Re-examination of the taxonomy of the macrobrachium australiense holthuis (Decapoda: Palaemonidae) species-complex: molecular evidence for a single species

The freshwater shrimp Macrobrachium australiense is distributed throughout the majority of inland, north-west, north-east and eastern drainages. Owing to the large amount of morphological divergence, both between and within catchments, this species has proven to be taxonomically difficult and, until recently, consisted of three separate species, each with subsequent subspecies. This study uses nucleotide sequences from the 16S rRNA mitochondrial gene region to investigate the genetic relationships between populations and confirm the taxonomic status of M. australiense. The results from sequencing an approximately 450-bp fragment from this gene region from M. australiense sampled from 12 locations across inland, eastern and northern Australia identified very little variation. The variation found between 16S M. australiense haplotypes is much less than that found between Macrobrachium species, indicating that it is in fact a single species. The results are concordant with a recent morphological revision of Australian species in which nominal taxa of the M. australiense complex were synonymised.

Mitochondrial 12S rRNA sequences support the existence of a third species of freshwater blackfish (Percicthyidae: Gadopsis) from south-eastern Australia

Fish of the genus Gadopsis are a distinctive component of the freshwater fish fauna of south-eastern Australia. Gadopsis marmoratus and G. bispinosus are the only two species recognised within the genus, with the former of uncertain taxonomic status, as it is thought to be composed of at least two distinct geographical forms based on morphological and allozyme data. The objective of this study was to investigate DNA sequence divergence in Gadopsis, especially in the western portion of its distribution, using an approximately 400 base pair fragment of the mitochondrial small subunit 12S rRNA gene region in order to reassess the taxonomy of the genus. Individuals from 11 locations were sequenced and confirm that G. marmoratus and G. bispinosus are genetically distinct, and further that the G. marmoratus complex consists of two divergent clades representing the previously identified northern and southern forms. The degree of divergence between the three Gadopsis clades was similar (5–6% nucleotide substitutions), suggesting that they diverged from a common ancestor at approximately the same period in geological time. These results are consistent with previous allozyme studies and highlight the usefulness of mitochondrial DNA data coupled with allozyme information for clarifying taxonomic boundaries in morphologically conservative aquatic organisms.

Phylogeny of the Australian freshwater crayfish Cherax destructor-complex (Decapoda:Parastacidae) inferred from four mitochondrial gene regions

The phylogenetic relationships among 32 individuals of Australian freshwater crayfish belonging to the Cherax destructor-complex were investigated using a dataset comprising sequences from four mitochondrial gene regions: the large subunit rRNA (16S rRNA), cytochrome oxidase I (COI), adenosine triphosphatase 6 (ATPase 6), and cytochrome oxidase III (COIII). A total of 1602 bp was obtained, and a combined analysis of the data produced a tree with strong support (bootstrap values 94–100%) for three divergent lineages, verifying the phylogenetic hypotheses of relationships within the C. destructor species-complex suggested in previous studies. Overall, sequences from the 16S rRNA gene showed the least variation compared to those generated from protein coding genes, which presented considerably greater levels of divergence. The level of divergence within C. destructor was found to be greater than that observed in other species of freshwater crayfish, but interspecific variation among species examined in the present study was similar to that reported previously.

Generating comprehensible summaries of rushes sequences based on robust feature matching

This paper describes our first attempt at tackling a pilot task in Trecvid: video summarization of rushes data [3]. Our method is based on the tight clustering produced via SIFT matching. In this first attempt, we try to examine how our approach performs without complex implementation in terms of concept detection and excerpt assembly (i.e, no picture-in-picture, split screen and special transitions). Although we do not perform very well in terms of concept inclusion, we rank very well in terms of the summary being easy to understand and relevancy of included segments.

An association rule analysis framework for complex physiological and genetic data

Physiological and genetic information has been critical to the successful diagnosis and prognosis of complex diseases. In this paper, we introduce a support-confidence-correlation framework to accurately discover truly meaningful and interesting association rules between complex physiological and genetic data for disease factor analysis, such as type II diabetes (T2DM). We propose a novel Multivariate and Multidimensional Association Rule mining system based on Change Detection (MMARCD). Given a complex data set u i (e.g. u 1 numerical data streams, u 2 images, u 3 videos, u 4 DNA/RNA sequences) observed at each time tick t, MMARCD incrementally finds correlations and hidden variables that summarise the key relationships across the entire system. Based upon MMARCD, we are able to construct a correlation network for human diseases. © 2012 Springer-Verlag.